By the year 2030 one-fifth of Americans will be 65 years or older, resulting in projected increases in health care spending of up to 25% (CDC, 2007; He et al., 2005). Declining mental and cognitive health is a primary component of increased health care costs, and a risk factor for diagnosis of Alzheimer’s Disease (AD) and death (NIH, 2007; van Gelder et al., 2007). Therefore, research supporting a greater understanding of the biological basis of cognitive aging and dementia, and important factors for their prevention, is essential for the development of low-cost prevention and treatment programs to address the aging crisis. For instance, although age is a prominent risk factor for AD, epidemiological studies have shown that lifestyle factors such as physical exercise significantly decrease age-related risks for cognitive impairment and AD (Barnes et al., 2003; Larson et al., 2006; Lindsay et al., 2002). Yet relatively little is known about precisely how exercise effects on the brain benefit human cognition (Cotman and Berchtold, 2002; Kramer and Erickson, 2007).
In this thesis I examine effects of physical activity on age-related deficits in brain function and cognition, followed by an examination of potential explanatory neurobiological factors. I examine brain function by assessing patterns of functional brain organization, or brain networks, using functional magnetic resonance imaging (fMRI). Using fMRI I demonstrate the use of multiple methods for measuring functional coherence of brain networks, and in turn, illustrate what various methods reveal about the positive effects of exercise on the aging brain. In the final study, I examine potential moderators and mediators for the positive effects of exercise on the brain, such as neurobiological markers of brain plasticity.
Normal aging is associated with a decline in cognitive functions, such as processing speed, episodic memory, and executive-control skills such as inhibition, planning, and working memory, and relative stability in semantic knowledge (Park and Reuter-Lorenz, 2009). Brain imaging studies have also revealed that the aging brain is characterized by increased variability in brain activation patterns which are often hard to explain by unified theories of cognitive aging (Greenwood, 2007a, b; Reuter-Lorenz and Lustig, 2005). In turn researchers have started to characterize functional brain networks comprised of regionally separate but temporally connected brain regions (Deluca et al., 2006; Fox et al., 2005), which could help uncover fundamental patterns of systems-level change associated with cognitive aging (Andrews-Hanna et al., 2007; Damoiseaux et al., 2008). One functional brain network, the default mode network (DMN), has received much attention for its capacity to predict individual differences in normal age-related cognitive decline (Andrews-Hanna et al., 2007; Damoiseaux et al., 2008) and clinical pathologies such as AD and MCI (Greicius et al., 2004; Lustig et al., 2003; Sorg et al., 2007).
Since both default mode network (DMN) function and increased aerobic fitness have been associated with improved cognitive performance and reduced incidence of AD among older adults. The first study in my dissertation investigated this link by examining the association between aerobic fitness, DMN function, and cognitive performance. Results showed significant age-related deficits in functional connectivity in both local and distributed DMN pathways. Interestingly, almost half of age-related functional disconnections showed increased connectivity as a function of aerobic fitness level. In this study I also examined the hypothesis that functional connectivity in the DMN is a source of variance in the relationship between aerobic fitness and cognition. Results demonstrated instances of both specific and global DMN connectivity mediating the relationship between fitness and cognition. This study provides the first evidence for functional connectivity in the DMN as a source of variance in the association between aerobic fitness and cognition, and results are discussed in the context of neurobiological theories of cognitive aging and disease (Voss et al., 2010a).
The second study in my dissertation extends the first study by (1) examining change in functional connectivity after a year-long randomized controlled trial of exercise training with elderly adults, and (2) comparing the effects of exercise on multiple brain networks including the DMN, two additional cognitively relevant brain networks, and primary motor and auditory sensory networks. Results showed that aerobic training improved the aging brain’s functional coherence selectively in higher-level cognitive networks. One year of walking increased functional connectivity between aspects of the frontal, posterior, and temporal cortices within the DMN and between the right and left prefrontal cortices in a Frontal Executive Network, two brain networks central to brain dysfunction in aging. Length of training was also an important factor. Significant effects in favor of the walking group were observed only after 12 months of training, compared to non-significant trends after six months. A non-aerobic stretching and toning group also showed increased functional connectivity in the DMN after six months and in a Frontal Parietal Network after 12 months, possibly reflecting experience-dependent plasticity. Finally, changes in functional connectivity were behaviorally relevant. Increased functional connectivity was associated with greater improvement in executive function. Thus, the second study provides the first evidence for exercise-induced functional plasticity in large-scale brain systems in the aging brain, using functional connectivity analysis, and offers new insight into the role of aerobic fitness in attenuating age-related brain dysfunction (Voss et al., 2010b).
In the third study I introduced another a class of methods for measuring functional connectivity in the brain, based on mathematical models that have been used for characterizing dynamic network behavior in self-organizing real-world systems, such as social networks or patterns of commercial airplane travel (Guimerà et al., 2005; Watts and Strogatz, 1998). Such methods provide a way to quantitatively describe the integration and segregation of communication patterns in the brain, and compare them to theoretical models of network communication, such as “small world” network models (Bullmore and Sporns, 2009). In this study I first use graph metrics to describe the associations between network topology, aging, and aerobic fitness in elderly adults and voxel-wise network metrics of communication in the brain. Second, I examine how exercise training affects such metrics of brain communication. This study was conducted with methodological support from Dr. Paul Laurienti (from the Department of Radiology at Wake Forest University), based on their published methodology (Hayasaka and Laurienti, 2009). Results and issues raised in this study also generalize to the study of individual differences in cognitive aging and training for future applications in my research. Overall, this study demonstrated that aging is associated with a qualitative shift in brain organization, which was associated with slowed processing speed and impaired working memory performance. Aerobic exercise was associated with attenuated progression of network markers of aging. Further, aerobic fitness was associated with a network metric reflecting network resilience to attack, and greater changes in aerobic fitness over one year were associated with increases in network resilience. The results of this study suggest that large-scale organizing properties of the brain are plastic to changes in health behaviors such as a one-year exercise program.
Finally, the fourth study examined the association between measures of brain connectivity and potential explanatory factors of the benefits of exercise on brain function, including neurobiological markers of brain plasticity measured from peripheral blood serum. Brain neurotrophins such as brain-derived neurotrophic factor (BDNF), insulin-like growth factor-1 (IGF-1), and vascular endothelial growth factor (VEGF) are considered primary molecular factors mediating effects of exercise on the aging brain (Cotman et al., 2007; Erickson et al., 2010), so the aim of this study was to link training-induced changes in BDNF, IGF-1, and VEGF with training-induced changes in functional brain connectivity as measured through univariate methods (Chapters 1 and 2) and multivariate methods (Chapter 3). However, since there were no changes in regional connectivity patterns in favor of the walking group, this study only examined the association between changes in connectivity shown in Chapter 2, and changes in neurobiological factors. The study also examined the extent to which baseline measures of peripheral growth factors was associated with change in functional connectivity in regional connections sensitive to exercise training. Results showed that although there were no group-level changes in growth factors as a function of the intervention, increased temporal lobe connectivity between the bilateral parahippocampus and the bilateral middle temporal gyrus was associated with increased BDNF, IGF-1, and VEGF for the aerobic walking group but not for the non-aerobic control group, and that greater baseline VEGF was associated with greater training-related increases in this functional connection. Results are consistent with animal models of exercise and the brain, but are the first to show in humans that increases in functional connectivity in the hippocampal and surrounding temporal lobe from aerobic exercise are promoted by changes in growth factors and may be augmented by greater baseline VEGF.